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%pip install pandas numpy plotly ipykernel --user
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import pandas as pd 
import plotly
import plotly.express as px
import numpy as np 

data = pd.read_csv("spotify-2023.csv")
len(data)
data
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track_name artist(s)_name artist_count released_year released_month released_day in_spotify_playlists in_spotify_charts streams in_apple_playlists ... bpm key mode danceability_% valence_% energy_% acousticness_% instrumentalness_% liveness_% speechiness_%
0 Seven (feat. Latto) (Explicit Ver.) Latto, Jung Kook 2 2023 7 14 553 147 141381703 43 ... 125 B Major 80 89 83 31 0 8 4
1 LALA Myke Towers 1 2023 3 23 1474 48 133716286 48 ... 92 C# Major 71 61 74 7 0 10 4
2 vampire Olivia Rodrigo 1 2023 6 30 1397 113 140003974 94 ... 138 F Major 51 32 53 17 0 31 6
3 Cruel Summer Taylor Swift 1 2019 8 23 7858 100 800840817 116 ... 170 A Major 55 58 72 11 0 11 15
4 WHERE SHE GOES Bad Bunny 1 2023 5 18 3133 50 303236322 84 ... 144 A Minor 65 23 80 14 63 11 6
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
948 My Mind & Me Selena Gomez 1 2022 11 3 953 0 91473363 61 ... 144 A Major 60 24 39 57 0 8 3
949 Bigger Than The Whole Sky Taylor Swift 1 2022 10 21 1180 0 121871870 4 ... 166 F# Major 42 7 24 83 1 12 6
950 A Veces (feat. Feid) Feid, Paulo Londra 2 2022 11 3 573 0 73513683 2 ... 92 C# Major 80 81 67 4 0 8 6
951 En La De Ella Feid, Sech, Jhayco 3 2022 10 20 1320 0 133895612 29 ... 97 C# Major 82 67 77 8 0 12 5
952 Alone Burna Boy 1 2022 11 4 782 2 96007391 27 ... 90 E Minor 61 32 67 15 0 11 5

953 rows × 24 columns

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released_year_group = data.groupby("released_year")
max_streams = released_year_group["streams"].idxmax()

new_data= data.loc[max_streams]
px.bar(new_data, x= "released_year", y="streams").show(renderer="notebook")
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data[data['artist(s)_name'].str.contains("Weeknd")]
data[data['track_name'].str.lower().str.contains("out of time")]
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track_name artist(s)_name artist_count released_year released_month released_day in_spotify_playlists in_spotify_charts streams in_apple_playlists ... bpm key mode danceability_% valence_% energy_% acousticness_% instrumentalness_% liveness_% speechiness_%
504 Out of Time The Weeknd 1 2022 1 7 3711 0 339659802 49 ... 93 NaN Minor 65 82 74 27 0 32 5

1 rows × 24 columns

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data["fire"] = data["energy_%"]-data['acousticness_%']+ data['valence_%']+ data['danceability_%']+ data['bpm']
fire_limit = np.median(data['fire'])
data["size"] = np.maximum(data["fire"],150)


plotly.express.scatter(data,x = "streams" , y = "fire", hover_data=["artist(s)_name","track_name","released_year",
"fire"] , title="isgob" ,color="fire" , size="size" ).show(renderer="notebook")
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